英語 IB 1A5 (=E1R86), 1L1 (=E1R05), 英語 IIB E2R40, 2011 L4

2011-11-10 (木)

英語

IB 1A5 (=E1R86), 1L1 (=E1R05) ,

IIB ^E2R40 , 2011

L4

http://clsl.hi.h.kyoto-u.ac.jp/~kkuroda/lectures/11B-KU/KU-2011B-L04- slides.pdf

黒田 航 (非常勤) substituting for 出口雅也 (非常勤)

連絡

1/2

✤ 日程

✤ 2011年11月24日(木)の講義を12月27日(火)に振替え

✤ 2012年1月12日(木)は休講

✤ 2012月1月9日(月)から13日(金)まで松江で開催される Global WordNet Associationに参加

✤ 2012年2月2日が最終日=ボーナス試験 (L=13に相当)

✤ 時間帯は自主的に変更してよいです

✤ 1,2時限目: 西棟12; 3時限目: 西棟03

✤ 欠席の扱い

✤ 明示的な上限はないですけど，欠席が多い方は不利です

✤ 今期に関しては最後のボーナス試験での挽回は不可能です

連絡

2/2

✤ Fast Readingのため

✤ 12月8日,15日,22日,27日は

✤ 共同東棟 22教室

✤ その後の二回は元の教室に戻る

講義資料

✤ 聴き取り用の教材は次の Web ページから入手可能

✤ http://clsl.hi.h.kyoto-u.ac.jp/~kkuroda/lectures/KU-11B.html

✤ 授業時間外での予習や復習に利用して下さい

✤ 特にボーナス試験対策には有効でしょう

✤ 速読に関して完全に同じことはできませんが，工夫 します

本日の予定

✤ 前半60分(休憩5分を含む)

✤ L3の結果の報告

✤ L3の正解の解説

✤ 後半30分

✤ TEDを使った聴き取り訓練

✤ Cynthia Breazeal: The Rise of Personal Robots (13分30秒)を通して視聴

✤ 後半9分の聴き取り

Date

L3

採点法

✤ 点数

✤ 完全正解 1.0 (◯で表示)

✤ 不完全解 0.5 (△で表示)

✤ 評価基準

✤ 素得点 S = ◯の数 + (△の数)/2

✤ 正答率 P = ◯の数/S

✤ 成績評価用の得点: S* = 100 × S/問題の総数 (e.g., 30)

✤ 採点誤りがあるかも知れません

✤ たし算を時々間違うので，該当者は報告して下さい

出題への評価

Q1: Quantity Q1: Quantity Q1: Quantity

Q1: Quantity Q2: DifficultyQ2: DifficultyQ2: DifficultyQ2: Difficulty

Av. Stdev Max Min Av. Stdev Max Min

1A5 3.21 0.51 4 2 2.38 0.65 3 1

2R 3.27 0.53 4 2 2.10 0.49 3 1

1L1 3.42 0.56 4 2 2.35 0.66 4 1

調査の回答は表に書いて下さい

L3

1A5, 2R, 1L1

✤ 参加者: 85人

✤ 平均: 69.68; 標準偏差: 14.06

✤ 最高: 97.73; 最低: 29.55

✤ 得点グループ数=3

L3

1A5

✤ 受講者数: 25人

✤ 平均: 73.00 [16.06/n] 点

✤ 標準偏差: 12.30 [ 2.71] 点

✤ 最高: 95.45/n [21.00] 点

✤ 最低: 47.73/n [ 7.00] 点

✤ n = 22

✤ 得点グループ数=3

L3

2R

✤ 受講者数: 28人

✤ 平均: 60.63 [13.34/n] 点

✤ 標準偏差: 12.90 [ 2.84] 点

✤ 最高: 81.82 [18.00/n] 点

✤ 最低: 22.55 [ 6.50/n] 点

✤ n = 22

✤ 得点グループ数=2

L3

1L1

✤ 受講者数: 32人

✤ 平均: 75.00 [16.50/n] 点

✤ 標準偏差: 12.70 [ 2.79] 点

✤ 最高: 97.73/n [21.50/n] 点

✤ 最低: 47.73/n [10.50/n] 点

✤ n = 22

✤ 得点グループ数=2

平均得点の変遷

(L3

)

L3

1A5, 2R, 1L1

✤ 参加者: 85人

✤ 平均値: 0.84

✤ 標準偏差: 0.10

✤ 最高値: 1.00; 最低値: 0.60

✤ 正答率のグループ数=2

L3

1A5

✤ 参加者: 25人

✤ 平均: 0.87; 標準偏差: 0.08

✤ 最高: 1.00; 最低: 0.67

✤ 正答率のグループ数=2?

L3

2R

✤ 参加者: 28人

✤ 平均: 0.80; 標準偏差: 0.11

✤ 最高: 0.97; 最低: 0.60

✤ 正答率のグループ数=2

L3

1L1

✤ 参加者: 32人

✤ 平均: 0.86; 標準偏差: 0.09

✤ 最高: 0.98; 最低: 0.64

✤ 正答率のグループ数=2

平均正答率の変遷

(L3

)

L3

誤りの傾向

✤ 1. fascinated ⇒ passed, fashioned, facinated

✤ 2. enrich ⇒ (in) which

✤ 3. Mars ⇒ Marth, Marks, mouse, earth

✤ 4. robots ⇒ about, it, us, happy

✤ 5. interacting

✤ 6. gave

✤ 7. lost ⇒ last(ed)

✤ 8. assume ⇒

NULL, soon, asume

✤ 9. with ⇒ without, which

✤ 10. been

✤ 11. developed ⇒ about, build,

developped

✤ 12. introducing ⇒ interesting,

interacting

✤ 13. find ⇒ fine

✤ 14. scary ⇒ scareley

✤ 15. cookies

✤ 16. learned

✤ 17. push ⇒ put

✤ 18. otherwise

✤ 19. using

✤ 20. use ⇒ uses

✤ 21. understand

✤ 22. matter ⇒ role, murder, now

聞き取りの心得その

2

✤ 例

✤ it is hoped that の発音は

✤ [ɨɗɨz hoʊp ðə]

✤ 母音前の有声化

✤ it is ⇒ [ɨɗɨz]

✤ look at the ⇒[lʊɡæðə]

✤ アメリカ英語の t の発音

✤ bottle ⇒ [bʌɔɗl]

✤ atoms = Adums ⇒ [æbɗəmz]

✤ 子音の前の語末子音の脱落

✤ hoped ⇒ hope [hoʊp]

✤ that ⇒ tha [ðə]

✤ th 音の変化

✤ that ⇒ nat [næ(t)]

01/13

✤ Ever since I was a little girl seeing Star Wars for the first time, I’ve been [1. fascinated] by this idea of personal

robots. And as a little girl, I loved the idea of a robot that interacted with us much more like a helpful, trusted

sidekick— something that would delight us, [2. enrich]

our lives and help us save a galaxy or two. So I knew

robots like that didn't really exist, but I knew I wanted to build them.

02/13

✤ So, 20 years passed— I am now a graduate student at MIT studying artificial intelligence, the year is 1997, and NASA

has just landed the first robot on [3. Mars]. But robots are still not in our home, ironically. And I remember thinking about all the reasons why that was the case. But one really struck me. Robotics had really been about interacting with things, not with people— certainly not in a social way that would be natural for us and would uh really help people accept [4.

robots] into our daily lives. For me, that was the white space, that's what robots could not do yet. And so that year, I started to build this robot, Kismet, the world’s first social robot.

03/13

✤ So, three years later— a lot of programming, working

with other graduate students in the lab— Kismet was ready to start [5. interacting] with people.

✤ Scientist: I wanna show you something.

✤ Kismet: (Nonsense).

✤ Scientist: This is a watch, watch that my girlfriend [6. gave] me.

✤ Kismet: (Nonsense).

✤ Scientist: Yeah, look, it’s got a little blue light in it too. I almost [7. lost] it this week.

04/13

✤ So Kismet interacted with people like kind of a non-

verbal child or pre-verbal child, which I [8. assume] was fitting because it was really the first of its kind. It didn’t speak language, but it didn’t matter.

✤ This little robot was somehow able to tap into something deeply social within us. And [9. with] that, the promise of an entirely new way we could interact with robots.

05/13

✤ So over the past several years I’ve [10. been] continuing to explore this interpersonal dimension of robots, now at the media lab with my own team of incredibly talented students.

And one of my favorite robots is Leonardo.

✤ We [11. developed] Leonardo in collaboration with Stan

Winston Studio. And so I wanna show you a special moment for me of Leo. Uh, this is Matt Berlin interacting with Leo, [12. introducing] Leo to a new object. And because it’s new, Leo doesn’t really know what to make of it. But sort of like us, he can actually learn about it from watching Matt’s reaction.

06/13

✤ Hello, Leo.

✤ Leo, this is Cookie Monster.

✤ Can you [13. find] Cookie Monster?

✤ Leo, Cookie Monster is very bad. He’s very bad, Leo.

✤ Cookie Monster is very, very bad.

✤ He’s a [14. scary] monster, wants to get your [15. cookies].

07/13

✤ Alright, so Leo and Cookie might have gotten off to a little bit of a rough start, but they get along great now.

✤ So what I’ve [16. learned] through building these systems is that robots are actually a really intriguing social technology.

Where it's actually their ability to [17. push] our social

buttons and to interact with us like a partner that is a core part of their functionality. And with that shift in thinking, we can now start to imagine new questions, new possibilities for robots that we might not have uh thought about [18.

otherwise].

08/13

✤ But what do I mean when I say “push our social

buttons?” Well, one of the things that we’ve learned is that, if we design these robots to communicate with us

[19. using] the same body language, the same sort of non- verbal cues that people use— like Nexi, our humanoid

robot is doing here— what we find is that people respond to robots a lot like they respond to people. People [20.

use] these cues to determine things like how persuasive someone is, how likable, how engaging, how trustworthy.

It turns out it's the same for robots.

09/13

✤ It’s turning out now that robots are actually becoming a really interesting new scientific tool to [21. understand]

human behavior. To answer questions like, how is it that, from a brief encounter, we’re able to make an estimate of how trustworthy another person is? Mimicry’s

believed to play a role, but how? Is it the mimicking of particular gestures that [22. matter]?

Date

TED

Cynthia Breazeal: The Rise of Personal Robots

✤ TEDの講演

✤ 約13分30秒: 1回目は4分30秒，2回目は9分

✤ 講演者

✤ Cynthia Breazeal は女性の米語の母語話者?

✤ 2000年に世界初の社交的ロボット Kismet を開発

✤ テーマ

✤ 社交的ロボット(social robot)の過去と未来